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Обучение искусству обработки информации об анализируемом объекте на основе раскрытия его особенностей

Обучение искусству обработки информации об анализируемом объекте на основе раскрытия его особенностей

Abstract

В статье говорится о статистических методах проведения глубокого анализа материала, который должен проводиться на основе представлений исследователя об определяющих с точки зрения поставленной задачи характеристик изучаемого явления или процесса. Конструирование в сознании аналитика образа предмета исследования обычно происходит с использованием метода аналогий, выработанные гипотезы впоследствии проверяются с помощью средств математики. Во время проведения математической обработки возникает эмерджентная система «модель – исследуемый материал». Совпадение предположений, свойств математической модели, природы изучаемых с ее помощью данных, закономерностей развития модели с тенденциями изменений реальных объектов приводит к большой надежности прогноза, к увеличению горизонта прогнозирования.

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Keywords

ИМИДЖ, ИНФОРМАТИВНОСТЬ ХАРАКТЕРИСТИК, СТАТИСТИЧЕСКИЕ МЕТОДЫ, МОДЕЛИРОВАНИЕ, ТЕОРИЯ РАСПОЗНАВАНИЯ ОБРАЗОВ, ИНТУИЦИЯ, ОБУЧЕНИЕ, ИСКУССТВО, САМООРГАНИЗАЦИЯ, СИСТЕМНЫЙ ПОДХОД, КЛАСТЕРНЫЙ АНАЛИЗ

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green